C4.5 has always been a good reference, and is considered in ML almost like a gold standard. For this reason, we would not like only to mimic it (through setting the right parameters for orange tree learner), but embed it just like it is in Quinlan's implementation [Janez never touched the functional code, just added an interface to oOrange and Python].

Are you saying that C4.5 is much better at it's style of machine learning than the equivalent module in Orange?

Or, that there isn't really anything like the C4.5. technique in Orange at all?

The reason I'm asking is that sometime in the next two months, I am going to add Python scripting support to my open source Robosapien Dance Machine project; which is a Delphi app. I would like to provide some automatic sensor data learning / classification routines via Orange; so the robot I'm controlling can make tricky decisions. Since both our projects are GPL that should not be a problem.

But it seems like the C4.5 technique is a good one for object classification, based on sensor data pattern matching? (Please correct me if I'm wrong). And I don't want to spend too much time with it (C4.5) if I can't distribute it to my users. I'm a big fan of "one-click" installs and telling them to go download and install C4.5. by themselves, AFTER they have installed my app is not what I intend to do.

So if there is something that is in good enough in Orange for my purposes, then I'll just use that instead. If I ever get permission from Sydney I'll change things, but I'm not holding my breath.

no, i just wanted to say that c4.5 is a nice reference. depending on classification task and peculiarities of your data, other machine learning algoritmh can perform much better (or much worse). there was a nice lesson at COIL 2000 challenge, where among many different algorithms, the simplest one (naive bayesian classifier) won [with a help of a little trick of constructing two new attributes, see http://www.liacs.nl/~putten/library/cc2000/].

in orange, classification tree learner should perform very similarly to c4.5 [use it through orngTree module, set sameMajorityPruning=1 and mForPruning=2].